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A Course on Small Area Estimation and Mixed Models
Methods, Theory and Applications in R
Taschenbuch von Domingo Morales (u. a.)
Sprache: Englisch

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Beschreibung
This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation. It presents the theory in a rigorous way and compares and contrasts various statistical methodologies, helping readers understand how to develop new methodologies for small area estimation. It also includes numerous sample applications of small area estimation techniques. The underlying R code is provided in the text and applied to four datasets that mimic data from labor markets and living conditions surveys, where the socioeconomic indicators include the small area estimation of total unemployment, unemployment rates, average annual household incomes and poverty indicators. Given its scope, the book will be useful for master and PhD students, and for official and other applied statisticians.
This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation. It presents the theory in a rigorous way and compares and contrasts various statistical methodologies, helping readers understand how to develop new methodologies for small area estimation. It also includes numerous sample applications of small area estimation techniques. The underlying R code is provided in the text and applied to four datasets that mimic data from labor markets and living conditions surveys, where the socioeconomic indicators include the small area estimation of total unemployment, unemployment rates, average annual household incomes and poverty indicators. Given its scope, the book will be useful for master and PhD students, and for official and other applied statisticians.
Über den Autor

Domingo Morales is a Professor of Statistics at the Miguel Hernández University of Elche, Spain. He has participated in two projects on Small Area Estimation (SAE) funded by the European Commission. Moreover, he has developed SAE methodologies and software for the Statistical Offices of Spain and Valencia. He has published more than 140 papers in statistics journals and taught courses on survey methodology and SAE at statistical institutes and universities. He has developed the R packages saery and mme.

María Dolores Esteban is a Professor of Statistics at the Miguel Hernández University of Elche, Spain. She has participated in two projects on Small Area Estimation (SAE) funded by the European Commission, and developed SAE methodologies and software for the Statistical Offices of Spain and Valencia. She has published more than 40 papers in statistics journals and taught courses on statistics and R at hospitals and universities. She has developed the R package saery.

Agustín Pérez is a Professor of Finance at the Miguel Hernández University of Elche, Spain. He has participated in one project on Small Area Estimation (SAE) funded by the European Commission. In addition, he has developed SAE methodologies and software for the Statistical Offices of Spain and Valencia. He has published more than 20 papers in statistics journals and taught courses on statistics and R at hospitals and universities. He has developed the R package saery.

TomᚠHobza is an Associate Professor of Statistics at the Czech Technical University in Prague, Czech Republic, where he works in the fields of Information Theory and Small Area Estimation (SAE). He has developed SAE methodologies and software with applications to labor market and living conditions survey data. He has published more than 20 papers in statistics journals and taught courses on statistics at universities and clinical research companies.

Zusammenfassung

Presents a rigorous mathematical description of statistical methodology for small area estimation

Compares and contrasts various statistical methodologies

Shows how to apply small area estimation techniques in surveys, providing the underlying R code

Inhaltsverzeichnis
1 Small Area Estimation.- 2 Design-based Direct Estimation.- 3 Design-based Indirect Estimation.- 4 Prediction Theory.- 5 Linear Models.- 6 Linear Mixed Models.- 7 Nested Error Regression Models.- 8 EBLUPs under Nested Error Regression Models.- 9 Mean Squared Error of EBLUPs.- 10 EBPs under Nested Error Regression Models.- 11 EBLUPs under Two-fold Nested Error Regression Models.- 12 EBPs under Two-fold Nested Error Regression Models.- 13 Random Regression Coefficient Models.- 14 EBPs under Unit-level Logit Mixed Models.- 15 EBPs under Unit-level Two-fold Logit Mixed Models.- 16 Fay-Herriot Models.- 17 Area-level Temporal Linear Mixed Models.- 18 Area-level Spatio-temporal Linear Mixed Models.- 19 Area-level Bivariate Linear Mixed Models.- 20 Area-level Poisson Mixed Models.- 21 Area-level Temporal Poisson Mixed Models.- A Some Useful Formulas.- Index.
Details
Erscheinungsjahr: 2022
Genre: Soziologie
Rubrik: Wissenschaften
Medium: Taschenbuch
Seiten: 620
Reihe: Statistics for Social and Behavioral Sciences
Inhalt: xx
599 S.
363 s/w Illustr.
10 farbige Illustr.
599 p. 373 illus.
10 illus. in color.
ISBN-13: 9783030637590
ISBN-10: 303063759X
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Morales, Domingo
Hobza, Tomá¿
Pérez, Agustín
Esteban, María Dolores
Auflage: 1st ed. 2021
Hersteller: Springer International Publishing
Statistics for Social and Behavioral Sciences
Maße: 235 x 155 x 34 mm
Von/Mit: Domingo Morales (u. a.)
Erscheinungsdatum: 14.03.2022
Gewicht: 0,925 kg
preigu-id: 121238975
Über den Autor

Domingo Morales is a Professor of Statistics at the Miguel Hernández University of Elche, Spain. He has participated in two projects on Small Area Estimation (SAE) funded by the European Commission. Moreover, he has developed SAE methodologies and software for the Statistical Offices of Spain and Valencia. He has published more than 140 papers in statistics journals and taught courses on survey methodology and SAE at statistical institutes and universities. He has developed the R packages saery and mme.

María Dolores Esteban is a Professor of Statistics at the Miguel Hernández University of Elche, Spain. She has participated in two projects on Small Area Estimation (SAE) funded by the European Commission, and developed SAE methodologies and software for the Statistical Offices of Spain and Valencia. She has published more than 40 papers in statistics journals and taught courses on statistics and R at hospitals and universities. She has developed the R package saery.

Agustín Pérez is a Professor of Finance at the Miguel Hernández University of Elche, Spain. He has participated in one project on Small Area Estimation (SAE) funded by the European Commission. In addition, he has developed SAE methodologies and software for the Statistical Offices of Spain and Valencia. He has published more than 20 papers in statistics journals and taught courses on statistics and R at hospitals and universities. He has developed the R package saery.

TomᚠHobza is an Associate Professor of Statistics at the Czech Technical University in Prague, Czech Republic, where he works in the fields of Information Theory and Small Area Estimation (SAE). He has developed SAE methodologies and software with applications to labor market and living conditions survey data. He has published more than 20 papers in statistics journals and taught courses on statistics at universities and clinical research companies.

Zusammenfassung

Presents a rigorous mathematical description of statistical methodology for small area estimation

Compares and contrasts various statistical methodologies

Shows how to apply small area estimation techniques in surveys, providing the underlying R code

Inhaltsverzeichnis
1 Small Area Estimation.- 2 Design-based Direct Estimation.- 3 Design-based Indirect Estimation.- 4 Prediction Theory.- 5 Linear Models.- 6 Linear Mixed Models.- 7 Nested Error Regression Models.- 8 EBLUPs under Nested Error Regression Models.- 9 Mean Squared Error of EBLUPs.- 10 EBPs under Nested Error Regression Models.- 11 EBLUPs under Two-fold Nested Error Regression Models.- 12 EBPs under Two-fold Nested Error Regression Models.- 13 Random Regression Coefficient Models.- 14 EBPs under Unit-level Logit Mixed Models.- 15 EBPs under Unit-level Two-fold Logit Mixed Models.- 16 Fay-Herriot Models.- 17 Area-level Temporal Linear Mixed Models.- 18 Area-level Spatio-temporal Linear Mixed Models.- 19 Area-level Bivariate Linear Mixed Models.- 20 Area-level Poisson Mixed Models.- 21 Area-level Temporal Poisson Mixed Models.- A Some Useful Formulas.- Index.
Details
Erscheinungsjahr: 2022
Genre: Soziologie
Rubrik: Wissenschaften
Medium: Taschenbuch
Seiten: 620
Reihe: Statistics for Social and Behavioral Sciences
Inhalt: xx
599 S.
363 s/w Illustr.
10 farbige Illustr.
599 p. 373 illus.
10 illus. in color.
ISBN-13: 9783030637590
ISBN-10: 303063759X
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Morales, Domingo
Hobza, Tomá¿
Pérez, Agustín
Esteban, María Dolores
Auflage: 1st ed. 2021
Hersteller: Springer International Publishing
Statistics for Social and Behavioral Sciences
Maße: 235 x 155 x 34 mm
Von/Mit: Domingo Morales (u. a.)
Erscheinungsdatum: 14.03.2022
Gewicht: 0,925 kg
preigu-id: 121238975
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